@InProceedings{SoterroniGalsRamo:2010:QsDeMe,
               author = "Soterroni, Aline Cristina and Galski, Luiz Roberto and Ramos, 
                         Fernando Manuel",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "The q-steepest descent method using the q-gradient vector",
            booktitle = "Anais...",
                 year = "2010",
               editor = "Rodrigues, Rita de C{\'a}ssia Meneses and Almeida, Wesley Gomes 
                         de and Assis, Talita Oliveira and Chalhoub, Ezzat Selim and 
                         Cortivo, F{\'a}bio Dall and Fran{\c{c}}a, Luis Fernando Amorim 
                         and Macau, Elbert Einstein Nehrer and Oliveira, Rudinei Martins de 
                         and Pillat, Valdir Gil and Santos, Laurita dos and Serpa, Dalila 
                         Ribeiro and Silva, Jos{\'e} Demisio Sim{\~o}es da and Silva, 
                         Marlon da",
         organization = "Workshop dos Cursos de Computa{\c{c}}{\~a}o Aplicada do INPE, 
                         10. (WORCAP).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "q-derivative, q-gradient vector, q-steepest descent method.",
             abstract = "Neste trabalho n{\'o}s utilizamos a q-derivada parcial de 
                         primeira ordem de uma fun{\c{c}}{\~a}o de n vari{\'a}veis para 
                         calcular o vetor q-gradiente e tomar a sua dire{\c{c}}{\~a}o 
                         negativa como a dire{\c{c}}{\~a}o de busca em m{\'e}todos de 
                         otimiza{\c{c}}{\~a}o irrestrita. N{\'o}s apresentamos uma 
                         q-vers{\~a}o do m{\'e}todo da m{\'a}xima descida denominado 
                         m{\'e}todo da q-m{\'a}xima descida. Essa q-vers{\~a}o retorna a 
                         sua vers{\~a}o cl{\'a}ssica sempre que o par{\^a}metro q, 
                         utilizado para calcular o vetor q-gradiente, {\'e} igual a 1. Os 
                         m{\'e}todos da m{\'a}xima descida e da q-m{\'a}xima descida 
                         s{\~a}o aplicados em uma fun{\c{c}}{\~a}o teste unimodal e uma 
                         fun{\c{c}}{\~a}o teste multimodal. ABSTRACT: In this work we 
                         make use of the first-order partial q-derivatives of a function of 
                         n variables to calculate the q-gradient vector and take the 
                         negative direction as the search direction of unconstrained 
                         optimization methods. We present a q-version of the classical 
                         steepest descent method called the q-steepest descent method. This 
                         q-version is reduced to the classical version whenever the 
                         parameter q, that is used to calculate the q-gradient vector, is 
                         equal to 1. We applied the classical steepest descent method and 
                         the q-steepest descent method to an unimodal and a multimodal test 
                         function.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos",
      conference-year = "20 e 21 out. 2010",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP8W/38B78H8",
                  url = "http://urlib.net/ibi/8JMKD3MGP8W/38B78H8",
           targetfile = "SoterroniAC.pdf",
                 type = "Tecnologia da informa{\c{c}}{\~a}o e extra{\c{c}}{\~a}o de 
                         informa{\c{c}}{\~o}es",
        urlaccessdate = "09 maio 2024"
}